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Author:

Geng, Shuqin (Geng, Shuqin.) | Li, Pengkun (Li, Pengkun.) | Yin, Xuzhou (Yin, Xuzhou.) | Lu, Hang (Lu, Hang.) | Zhu, Ronghao (Zhu, Ronghao.) | Cao, Wenhua (Cao, Wenhua.) | Nie, Jingyao (Nie, Jingyao.)

Indexed by:

EI Scopus

Abstract:

This letter studies the problem of anti-jamming power control in wireless communication systems where users do not know the game model. When the transmission loss and other parameters are unknown, we use the Q-learning algorithm to build a wireless communication system with anti-jamming power control game model. The user utility function and SINR under channel gain are simulated and compared, which proves the better anti-jamming performance of the algorithm. © 2022 IEEE.

Keyword:

Learning algorithms Reinforcement learning Power control Security systems Jamming

Author Community:

  • [ 1 ] [Geng, Shuqin]Beijing University of Technology, Faculty of Information Technology, Beijing, China
  • [ 2 ] [Li, Pengkun]Beijing University of Technology, Faculty of Information Technology, Beijing, China
  • [ 3 ] [Yin, Xuzhou]Peking University, College of Software and Microelectronics, Beijing, China
  • [ 4 ] [Lu, Hang]Beijing University of Technology, Faculty of Information Technology, Beijing, China
  • [ 5 ] [Zhu, Ronghao]Beijing University of Technology, Faculty of Information Technology, Beijing, China
  • [ 6 ] [Cao, Wenhua]Beijing University of Technology, Faculty of Information Technology, Beijing, China
  • [ 7 ] [Nie, Jingyao]Beijing University of Technology, Faculty of Information Technology, Beijing, China

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Source :

Year: 2022

Page: 182-185

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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